ArticleNature reviews. Nephrology2020
Artificial intelligence in nephropathology.
Article in Nature reviews. Nephrology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
14 citing papers in PubMed.
- Artificial Intelligence for Diagnostic Pathology in Nephrology.Journal of the American Society of Nephrology : JASN · 2026Article
- Deep learning-based quantitative analysis of glomerular morphology in IgA nephropathy whole slide images and its prognostic implications.Scientific reports · 2025Article
- Vision transformer introduces a new vitality to the classification of renal pathology.BMC nephrology · 2024Article
- tRigon: an R package and Shiny App for integrative (path-)omics data analysis.BMC bioinformatics · 2024Article
- Next-Generation Morphometry for pathomics-data mining in histopathology.Nature communications · 2023Article
- Banff Digital Pathology Working Group: Image Bank, Artificial Intelligence Algorithm, and Challenge Trial Developments.Transplant international : official journal of the European Society for Organ Transplantation · 2023Article
- Machine learning to predict end stage kidney disease in chronic kidney disease.Scientific reports · 2022Article
- Multi-Task Learning-Based Immunofluorescence Classification of Kidney Disease.International journal of environmental research and public health · 2021Article
- How will artificial intelligence and bioinformatics change our understanding of IgA Nephropathy in the next decade?Seminars in immunopathology · 2021Review
- Artificial intelligence and algorithmic computational pathology: an introduction with renal allograft examples.Histopathology · 2021Review
- Opportunities in the cloud or pie in the sky? Current status and future perspectives of telemedicine in nephrology.Clinical kidney journal · 2021Review
- New Aspects of Kidney Fibrosis-From Mechanisms of Injury to Modulation of Disease.Frontiers in medicine · 2021Review
- Development and evaluation of deep learning-based segmentation of histologic structures in the kidney cortex with multiple histologic stains.Kidney international · 2021Article
- [Digital nephrology].Der nephrologe · 2021Article
Corrections and comments
- Comment on
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
PubMed holds no abstract for this paper.
Indexed as
Identifiers
31597956What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.